Forthcoming and Online First Articles

International Journal of Advanced Mechatronic Systems

International Journal of Advanced Mechatronic Systems (IJAMechS)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression "in press". For example: Smith, J. (in press). Article Title. Journal Title.

Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase.

Online First articles are published online here, before they appear in a journal issue. Online First articles are fully citeable, complete with a DOI. They can be cited, read, and downloaded. Online First articles are published as Open Access (OA) articles to make the latest research available as early as possible.

Open AccessArticles marked with this Open Access icon are Online First articles. They are freely available and openly accessible to all without any restriction except the ones stated in their respective CC licenses.

Register for our alerting service, which notifies you by email when new issues are published online.

We also offer which provide timely updates of tables of contents, newly published articles and calls for papers.

International Journal of Advanced Mechatronic Systems (2 papers in press)

Regular Issues

  • Scratch detection system of the inner surface of super long gas cylinder based on VGG-16 neural networks   Order a copy of this article
    by Baocheng He, Linguang Li, Shijie Ren, Dianwei Qian 
    Abstract: Aiming at the problems of difficulty and low detection accuracy in manual detection of scratches on the inner surface of ultra-long energy storage gas cylinders in the aerospace industry, a detection system for scratches on the inner surface of ultra-long gas cylinders based on VGG-16 neural network is designed. In this paper, VGG-16 recognition model is innovatively proposed to apply to the application of scratch detection. Compared with the ordinary detection model to detect the required target from the complex background, this article first processes the image acquired by the image acquisition module into a single binary image with a scratched area and a non-scratched area. The VGG-16 recognition model learns the characteristics of the scratches, so as to recognise the scratches under the ordinary background, and achieve the purpose of scratch detection. The results show that the accuracy rate of the scratch detection on the inner surface of gas cylinders reaches 98.5%, which greatly improves the accuracy rate of the scratch detection compared with the previous manual detection methods.
    Keywords: scratch test; image processing; neural network; linear array camera.
    DOI: 10.1504/IJAMECHS.2022.10044450
  • SVM based fault detection for double layered tank system by considering ChangeFinder's characteristics   Order a copy of this article
    by Yosuke Furukawa, Mingcong Deng 
    Abstract: In this paper, a fault detection scheme for a tank system using support vector machine (SVM) combined with ChangeFinder, both are machine learning methods, is studied. SVM can detect faults on a nonlinear system, but it can be late because SVM cannot recognise the nature of the time series. Combination with ChangeFinder enables SVM to recognise the nature of time series, and early detection using SVM becomes possible. Simulations and experiments assuming the temperature sensor fault case for the temperature control system of the tank system have been done and 5 s reduction of detection time was confirmed. In addition to the situation of the tank system, the sine wave input showed the effectiveness of the proposed method for general input. In addition, the superiority of the proposed method over ChangeFinder in an experimental environment was confirmed.
    Keywords: nonlinear control; fault detection; fault tolerance; ChangeFinder; support vector machine; SVM.
    DOI: 10.1504/IJAMECHS.2022.10044457